BEYONDPLANCK III. Commander3

• Published in: Astronomy and astrophysics (Berlin) Vol. 675; p. A3
• Main Authors: Galloway, M., Andersen, K. J., Aurlien, R., Banerji, R., Bersanelli, M., Bertocco, S., Brilenkov, M., Carbone, M., Colombo, L. P. L., Eriksen, H. K., Eskilt, J. R., Foss, M. K., Franceschet, C., Fuskeland, U., Galeotta, S., Gerakakis, S., Gjerløw, E., Hensley, B., Herman, D., Iacobellis, M., Ieronymaki, M., Ihle, H. T., Jewell, J. B., Karakci, A., Keihänen, E., Keskitalo, R., Maggio, G., Maino, D., Maris, M., Mennella, A., Paradiso, S., Partridge, B., Reinecke, M., San, M., Suur-Uski, A.-S., Svalheim, T. L., Tavagnacco, D., Thommesen, H., Watts, D. J., Wehus, I. K., Zacchei, A.
• Format: Journal Article
• Language: English; Norwegian
• Published: United States EDP Sciences 28.06.2023
• Subjects: ASTRONOMY AND ASTROPHYSICS; cosmic background radiation; MATHEMATICS AND COMPUTING; methods: data analysis; methods: numerical
• ISSN: 0004-6361; 1432-0746
• DOI: 10.1051/0004-6361/202243137

We describe the computational infrastructure for end-to-end Bayesian cosmic microwave background (CMB) analysis implemented by the BeyondPlanck Collaboration. The code is called Commander3 . It provides a statistically consistent framework for global analysis of CMB and microwave observations and may be useful for a wide range of legacy, current, and future experiments. The paper has three main goals. Firstly, we provide a high-level overview of the existing code base, aiming to guide readers who wish to extend and adapt the code according to their own needs or re-implement it from scratch in a different programming language. Secondly, we discuss some critical computational challenges that arise within any global CMB analysis framework, for instance in-memory compression of time-ordered data, fast Fourier transform optimization, and parallelization and load-balancing. Thirdly, we quantify the CPU and RAM requirements for the current B EYOND P LANCK analysis, finding that a total of 1.5 TB of RAM is required for efficient analysis and that the total cost of a full Gibbs sample for LFI is 170 CPU-hrs, including both low-level processing and high-level component separation, which is well within the capabilities of current low-cost computing facilities. The existing code base is made publicly available under a GNU General Public Library (GPL) license.